Short-range forecasts for periods on the order of hours to days and up to two weeks ahead are necessary to smoothly run transmission and distribution systems, plan maintenance, protect infrastructure and allocate units. In particular, forecasting the renewable energy resources on a day-to-day basis enables integration of increasing capacities of these variable resources. This chapter describes the basics of this short-range forecasting, beginning with the observation-based ``nowcasting'' of the first 15 minutes and ranging up to two weeks using numerical weather prediction. We discuss how blending multiple forecasts can increase accuracy and how probabilistic forecasts are being used to quantify the forecast uncertainty.
%0 Book Section
%1 Haupt2018
%A Haupt, Sue Ellen
%B Weather & Climate Services for the Energy Industry
%C Cham
%D 2018
%E Troccoli, Alberto
%I Springer International Publishing
%K energy nowcasting nwp renewables review solar textbook wind
%P 97--107
%R 10.1007/978-3-319-68418-5_7
%T Short-Range Forecasting for Energy
%U https://doi.org/10.1007/978-3-319-68418-5_7
%X Short-range forecasts for periods on the order of hours to days and up to two weeks ahead are necessary to smoothly run transmission and distribution systems, plan maintenance, protect infrastructure and allocate units. In particular, forecasting the renewable energy resources on a day-to-day basis enables integration of increasing capacities of these variable resources. This chapter describes the basics of this short-range forecasting, beginning with the observation-based ``nowcasting'' of the first 15 minutes and ranging up to two weeks using numerical weather prediction. We discuss how blending multiple forecasts can increase accuracy and how probabilistic forecasts are being used to quantify the forecast uncertainty.
%@ 978-3-319-68418-5
@inbook{Haupt2018,
abstract = {Short-range forecasts for periods on the order of hours to days and up to two weeks ahead are necessary to smoothly run transmission and distribution systems, plan maintenance, protect infrastructure and allocate units. In particular, forecasting the renewable energy resources on a day-to-day basis enables integration of increasing capacities of these variable resources. This chapter describes the basics of this short-range forecasting, beginning with the observation-based ``nowcasting'' of the first 15 minutes and ranging up to two weeks using numerical weather prediction. We discuss how blending multiple forecasts can increase accuracy and how probabilistic forecasts are being used to quantify the forecast uncertainty.},
added-at = {2018-10-10T12:14:36.000+0200},
address = {Cham},
author = {Haupt, Sue Ellen},
biburl = {https://www.bibsonomy.org/bibtex/27cd97babf17b8876072b254db11e7754/pbett},
booktitle = {Weather {\&} Climate Services for the Energy Industry},
description = {Short-Range Forecasting for Energy | SpringerLink},
doi = {10.1007/978-3-319-68418-5_7},
editor = {Troccoli, Alberto},
interhash = {bc878a054b10e6b47c3ca97c8a779fdb},
intrahash = {7cd97babf17b8876072b254db11e7754},
isbn = {978-3-319-68418-5},
keywords = {energy nowcasting nwp renewables review solar textbook wind},
pages = {97--107},
publisher = {Springer International Publishing},
timestamp = {2018-10-10T12:14:36.000+0200},
title = {Short-Range Forecasting for Energy},
url = {https://doi.org/10.1007/978-3-319-68418-5_7},
year = 2018
}